AgTech - Precision Agriculture: Lecture 3
Overview
- Precision Agriculture aims to manage soil variability to improve crop yield and resource use.
- Key components: soil sensing, grid sampling, EMI/EM38, site-specific management, controlled traffic farming (CTF), variable rate (VR) applications.
Why consider soil variability?
- Soils vary across the landscape in nutrient and water-holding capacity.
- Variability leads to differences in crop yield and quality.
How can we measure soil variation?
- Use gridded soil sampling with a grid; GPS locates sampling sites.
- Grid sampling is effective but can be costly.
Gridded soil sampling to produce maps
- Superimpose a grid over an area; sample each cell (GPS-based locations).
- Creates soil variability maps used for decision making.
Soil Phosphorus (Colwell P)
- Colwell P ranges indicate phosphorus availability in mg/kg.
- Categories (example):
- Sample points feed the Colwell P map used for targeted P management.
Electromagnetic Induction (EMI)
- EMI sensors measure electromagnetic conductivity (ECa) in the soil.
- Apparent soil conductivity (ECa) often correlates with:
- Salinity
- Texture (clay content)
- Soil water content
- EMI surveys provide conductivity maps, not direct soil type maps.
EM38 soil survey
- EM38 delivers conductivity data over paddocks to map variability.
- Conductivity values are used to infer soil properties and guide management.
How EMI/EM38 works
- EMI uses a transmitting coil and a receiving coil.
- Transmitter emits a primary magnetic field; soil generates a secondary magnetic field detected by the receiver.
- The measured signal strength is related to soil conductivity (ECa).
How does it work? (concepts)
- Primary field induces eddy currents in soil.
- Secondary field is sensed; the strength is proportional to ECa.
- This relates to ion content (salinity), texture, and moisture.
Applications of the EM38
- Map soil variability across paddocks.
- Guide variable irrigation and drainage planning.
- Salinity monitoring and drainage profiling.
- Contouring, levelling, and irrigation scheduling.
The Importance of Calibration… Ground Truthing
- Sensor maps show variability but are not enough alone for maps.
- Calibrate sensor data to actual soil values via soil sampling.
- Sensor maps can direct sampling regimes and reduce the number of samples needed.
Example – EM38 used to site C-Probes for Irrigation
- EM38 data can be used to schedule irrigations based on soil variability.
Where should they site the probe?
- Surface/furrow irrigation context: placement should consider soil type and plant growth.
- A map of soil types can aid in site selection and irrigation decisions.
Where should they go in the paddock?
- Use EM38 to classify areas by soil texture/quality (e.g., heavy, medium, light soils).
- Example mapping: heavy soil (EM38 ≈ 200 mS/m), light soil (≈ 100 mS/m), medium (≈ 150 mS/m).
Precision Agriculture Application Examples
- Controlled traffic farming (CTF)
- Interrow sowing
- Weed management
Controlled-traffic farming (CTF)
- CT farming guides all machines to follow the same wheel tracks repeatedly.
- Requires 2–5 cm positioning accuracy (RTK or PPP).
Why control wheel traffic?
- First tyre pass causes ~90% of soil compaction.
- Reduces cumulative soil damage from multiple passes.
Why control wheel traffic? (more context)
- Wheels drive over 20% (best no-till) to 250% (worst horticulture) of paddock area per year.
- Reducing traffic helps prevent erosion and consolidate soil structure.
Benefits of CTF
- Reduces fuel consumption (up to 50\%).
- Improves traction and minimizes overlap during operations.
Opportunity in wetter conditions
- Controlled traffic allows machinery operation in wetter conditions without excessive soil damage.
Guidance ~ 2 cm
- The aim is precise guidance (approx. 2 cm) for traffic lanes.
- Benefits include erosion protection, better water infiltration, improved establishment and yields.
Guidance is about control
- Guidance refers to control of traffic and operations, not autonomy.
- Intelligent systems are still needed to manage decisions.
Variable Rate (VR)
- Modern machines can adjust input rates across a paddock:
- Seed sowing rate
- Growth regulators
- Fertilisers
- Herbicides/Pesticides
- Controlled by VR controllers and decision maps.
Why VR?
- Save input costs and/or optimise yield.
- Traditional front-loaded N applications can cause leaching after rainfall or denitrification during waterlogging; not matching season variability.
- VR helps mitigate dead zones and uneven performance.
VR – how it’s done
- VR requires knowing when/where to adjust rates.
- Sensors used include:
- Proximal NDVI (in-season plant reflectance)
- Satellite NDVI
- Yield monitors (historic harvest)
- Sensor measurements generate variability maps used to set application rates.
Summary video
- Reference: https://www.youtube.com/watch?v=lz76L7qjxzM
What I want you to know
- Know some applications of precision agriculture.
- Understand what the EM38 is and how it works.
- Understand variable rate and site-specific management.
- Know how this information can be used by a farmer.
Exam preparation (revision prompts)
- What are the 3 types of variability?
- What is a type of sensor used for plant sensing? How does it work?
- Why is the reflectance signature of different plants important?
- What can the farmer use this information for?
- How does measuring soil variability work?
- What can the data be used for?
- What are some types of precision livestock (PL) technology?
- What are the benefits and challenges of the different PL technologies?
- How does GNSS work?
- Why are there different types of GNSS?